Reconstruction and Subgaussian Operators in Asymptotic Geometric Analysis

Abstract

We present a randomized method to approximate any vector from a set. The data one is given is the set T, vectors of and k scalar products, where are i.i.d. isotropic subgaussian random vectors in R, and N. We show that with high probability, any which is Show more